IDEAS home Printed from https://ideas.repec.org/p/aly/journl/202212.html
   My bibliography  Save this paper

An analysis on complaint behaviour of hotel guests in Italy

Author

Listed:
  • Farzaneh Soleimani Zoghi

    (SRH Berlin University of Applied Sciences, Germany)

Abstract

The main purpose of this study is to analyse the complaint behaviour of hotel guests based on their online reviews. Furthermore, the importance of hotel responses to complaints and its impact on reducing customer dissatisfaction will be highlighted. The study is designed as explorative and inductive. The methodological approach is a content analysis on secondary data and the data used in this research is scraped from Booking.com. Tableau Data Analytics (2020.4) has been used to analysis the large amount of data in the database. The findings of the study underline the importance of monitoring and responding online reviews, since it is the most common place for hotel guests to write their complaint or feedback. Furthermore, the results call hotel managers attention to measure reputation risk level from the online reviews and take necessary action when its threshold is exceeded in service related areas.

Suggested Citation

  • Farzaneh Soleimani Zoghi, "undated". "An analysis on complaint behaviour of hotel guests in Italy," Review of Socio - Economic Perspectives 202212, Reviewsep.
  • Handle: RePEc:aly:journl:202212
    DOI: https://doi.org/10.19275/RSEP132
    as

    Download full text from publisher

    File URL: https://reviewsep.com/wp-content/uploads/2022/09/3_FARZANEH.pdf
    Download Restriction: no

    File URL: https://reviewsep.com/?page_id=1891
    Download Restriction: no

    File URL: https://libkey.io/https://doi.org/10.19275/RSEP132?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Xiangbin Yan & Jing Wang & Michael Chau, 2015. "Customer revisit intention to restaurants: Evidence from online reviews," Information Systems Frontiers, Springer, vol. 17(3), pages 645-657, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Raghav Pavan Karumur & Tien T. Nguyen & Joseph A. Konstan, 2018. "Personality, User Preferences and Behavior in Recommender systems," Information Systems Frontiers, Springer, vol. 20(6), pages 1241-1265, December.
    2. Wei-Lun Chang & Yi-Pei Chen, 2019. "Way too sentimental? a credible model for online reviews," Information Systems Frontiers, Springer, vol. 21(2), pages 453-468, April.
    3. Park, Eunil, 2019. "Motivations for customer revisit behavior in online review comments: Analyzing the role of user experience using big data approaches," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 14-18.
    4. Yi Luo & Xiaowei Xu, 2019. "Predicting the Helpfulness of Online Restaurant Reviews Using Different Machine Learning Algorithms: A Case Study of Yelp," Sustainability, MDPI, vol. 11(19), pages 1-17, September.
    5. Chul Woo Yoo, 2020. "An Exploration of the Role of Service Recovery in Negative Electronic Word-of-Mouth Management," Information Systems Frontiers, Springer, vol. 22(3), pages 719-734, June.
    6. Heng Tang & Chang Boon Patrick Lee & Kwee Keong Choong, 2017. "Consumer decision support systems for novice buyers – a design science approach," Information Systems Frontiers, Springer, vol. 19(4), pages 881-897, August.
    7. Seung-Hun Shin & Sung-Byung Yang & Kichan Nam & Chulmo Koo, 2017. "Conceptual foundations of a landmark personality scale based on a destination personality scale: Text mining of online reviews," Information Systems Frontiers, Springer, vol. 19(4), pages 743-752, August.
    8. Sin, Geonyul & Ryu, Min Ho, 2024. "A study on the performance of Korea's traditional market support project using eWOM: Focusing on Busan, South Korea," 24th ITS Biennial Conference, Seoul 2024. New bottles for new wine: digital transformation demands new policies and strategies 302515, International Telecommunications Society (ITS).
    9. Elvira Ismagilova & Emma L. Slade & Nripendra P. Rana & Yogesh K. Dwivedi, 2020. "The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis," Information Systems Frontiers, Springer, vol. 22(5), pages 1203-1226, October.
    10. Zhuolan Bao & Wenwen Li & Pengzhen Yin & Michael Chau, 2021. "Examining the impact of review tag function on product evaluation and information perception of popular products," Information Systems and e-Business Management, Springer, vol. 19(2), pages 517-539, June.
    11. Lin Xiao & Chuanmin Mi & Yucheng Zhang & Jing Ma, 2019. "Examining Consumers’ Behavioral Intention in O2O Commerce from a Relational Perspective: an Exploratory Study," Information Systems Frontiers, Springer, vol. 21(5), pages 1045-1068, October.
    12. Elvira Ismagilova & Emma L. Slade & Nripendra P. Rana & Yogesh K. Dwivedi, 0. "The Effect of Electronic Word of Mouth Communications on Intention to Buy: A Meta-Analysis," Information Systems Frontiers, Springer, vol. 0, pages 1-24.
    13. Juheng Zhang & Selwyn Piramuthu, 2018. "Product recommendation with latent review topics," Information Systems Frontiers, Springer, vol. 20(3), pages 617-625, June.
    14. Mengyue Wang & Xin Li & Patrick Y. K. Chau, 2021. "Leveraging Image-Processing Techniques for Empirical Research: Feasibility and Reliability in Online Shopping Context," Information Systems Frontiers, Springer, vol. 23(3), pages 607-626, June.
    15. Kawaljeet Kaur Kapoor & Kuttimani Tamilmani & Nripendra P. Rana & Pushp Patil & Yogesh K. Dwivedi & Sridhar Nerur, 2018. "Advances in Social Media Research: Past, Present and Future," Information Systems Frontiers, Springer, vol. 20(3), pages 531-558, June.
    16. Youngseok Choi & Habin Lee, 2017. "Data properties and the performance of sentiment classification for electronic commerce applications," Information Systems Frontiers, Springer, vol. 19(5), pages 993-1012, October.
    17. Shawn Berry, 2024. "Fake Google restaurant reviews and the implications for consumers and restaurants," Papers 2401.11345, arXiv.org, revised Apr 2024.
    18. Heng Tang & Chang Boon Patrick Lee & Kwee Keong Choong, 0. "Consumer decision support systems for novice buyers – a design science approach," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
    19. Luvai Motiwalla & Amit V. Deokar & Surendra Sarnikar & Angelika Dimoka, 2019. "Leveraging Data Analytics for Behavioral Research," Information Systems Frontiers, Springer, vol. 21(4), pages 735-742, August.
    20. Nilashi, Mehrbakhsh & Ahmadi, Hossein & Arji, Goli & Alsalem, Khalaf Okab & Samad, Sarminah & Ghabban, Fahad & Alzahrani, Ahmed Omar & Ahani, Ali & Alarood, Ala Abdulsalam, 2021. "Big social data and customer decision making in vegetarian restaurants: A combined machine learning method," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).

    More about this item

    Keywords

    complaint behaviour; online reviews; customer satisfaction; reputation risk; hospitality business;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M16 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - International Business Administration
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aly:journl:202212. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Veysel KAYA (email available below). General contact details of provider: https://edirc.repec.org/data/degraus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.